A method for rapid, non-destructive determination of whether a water product is frozen stored

Abstract

This invention discloses a rapid, non-destructive method for determining whether aquatic products have undergone frozen storage, relating to the field of bioelectrical impedance analysis. The method includes: applying multi-frequency excitation signals to the muscle tissue of the aquatic product using a non-deformation, pressure-based contact method, and collecting its impedance spectrum data within a preset frequency range; extracting frequency domain feature parameters reflecting the integrity of the cell membrane barrier based on the impedance spectrum data, wherein the frequency domain feature parameters include at least the variation characteristics of the impedance amplitude in the low-frequency band relative to the high-frequency band; comparing the frequency domain feature parameters with a discrimination criterion constructed based on the specific impedance dispersion characteristics caused by cell membrane rupture due to frozen storage damage, and determining whether the aquatic product has undergone frozen storage based on the comparison results. This application's solution simultaneously meets the technical requirements of speed, accuracy, and ease of operation while ensuring non-destructive testing.

Description

Technical Field

[0001] This invention relates to the field of bioelectrical impedance analysis, and in particular to a rapid, non-destructive method for determining whether aquatic products have been frozen. Background Technology

[0002] The freshness of aquatic products directly determines their edible quality and commercial value. Based on preservation methods, commercially available aquatic products are mainly divided into two categories: "fresh fish" (chilled but not frozen) and "thawed fish" (frozen and then thawed). Fresh fish, under low-temperature refrigeration conditions, can maintain the integrity of its cell structure, and its muscle tissue and moisture are well preserved, but it has a short shelf life and a higher price. Thawed fish, although it can be stored for a long time, suffers irreversible mechanical damage to its muscle tissue due to the formation and growth of ice crystals during freezing. After thawing, it often experiences problems such as juice loss, loose texture, and a significant decline in quality. The two types of fish have substantial differences in market positioning and quality characteristics. Currently, there is a phenomenon in the market of thawed fish being sold as fresh fish. Because the two look similar, conventional methods are difficult to use to effectively distinguish them, seriously infringing on consumer rights and disrupting market order. The quality deterioration caused by freezing is essentially due to the destruction of the muscle's ultrastructure caused by the phase change of water, a process that fresh fish does not undergo. This difference in microstructure provides a theoretical basis for physicochemical identification. The electrical impedance detection technology based on the difference in conductivity of fish tissue before and after freeze-thaw cycles reflects changes in the internal structure of the tissue by measuring specific electrical parameters. It has the potential advantages of being fast, non-destructive, and convenient for on-site testing, providing a promising technical direction for this field.

[0003] To address the challenge of distinguishing between fresh and frozen fish, existing technologies suffer from the following limitations: sensory identification relies on the experience and judgment of the testing personnel, making it susceptible to subjective factors and species differences. It also has a high misjudgment rate for short-term frozen samples, hindering objective and stable identification. Chemical detection methods based on protein electrophoresis, enzyme activity assays, or metabolite analysis, while scientifically sound, are cumbersome, time-consuming, and require reagents, making them unsuitable for on-site screening in the distribution process. Physical detection methods based on textural properties or water content suffer from significant individual sample variations, resulting in insufficient accuracy and universality of results. These methods generally suffer from slow detection speeds and sample destructiveness, making it difficult to simultaneously meet the technical requirements of being rapid, non-destructive, and easy to apply on-site. Therefore, based on these challenges, this invention proposes a rapid and non-destructive method for determining whether aquatic products have been frozen. Summary of the Invention

[0004] To address the aforementioned problems, the present invention aims to provide a rapid and non-destructive method for determining whether aquatic products have been frozen. This method overcomes the technical shortcomings of existing aquatic product freshness identification technologies, such as slow detection speed, destructive nature, and difficulty in meeting the needs of rapid on-site screening in the distribution process. It provides a rapid, non-destructive, and easy-to-operate method for determining whether aquatic products have undergone freezing, thereby effectively solving the market problem of thawed fish being passed off as fresh fish and ensuring the authenticity of aquatic product quality.

[0005] To achieve the above objectives, this invention provides a rapid and non-destructive method for determining whether aquatic products have undergone frozen storage. This method employs a non-deformation, pressure-contact four-electrode measurement configuration, applying multi-frequency excitation signals to the muscle tissue of the aquatic product under test, and acquiring electrical impedance spectrum data within a preset frequency range. During acquisition, an automatic gain control module dynamically adapts the excitation signal amplitude to ensure signal quality. Based on the acquired electrical impedance spectrum data, frequency domain characteristic parameters reflecting cell membrane barrier integrity are extracted, including at least the low-frequency impedance amplitude and its variation characteristics relative to the high-frequency band. These characteristic parameters are compared with a pre-constructed discrimination model, which is based on the specific impedance dispersion characteristics caused by cell membrane rupture due to frozen storage damage. By analyzing whether a specific decrease occurs in the low-frequency impedance amplitude, it is determined whether the aquatic product under test has undergone frozen storage, thereby converting microscopic differences in cell structural integrity into quantitatively measurable macroscopic electrical signals, achieving rapid and non-destructive automatic discrimination.

[0006] In a first aspect, the present invention provides a rapid and non-destructive method for determining whether aquatic products have been frozen, comprising: Using a non-deformable compression contact method where the contact pressure is provided solely by the probe's own weight, a multi-frequency composite excitation signal is applied to the muscle tissue of the aquatic product under test through a four-electrode measurement configuration. The excitation signal is injected through the outer electrode, and the response signal is picked up by the inner electrode. During the acquisition process, the signal response intensity is monitored in real time, and the amplitude of the excitation signal is dynamically adapted. The response signal at each frequency component is extracted synchronously using a phase-synchronous demodulation method, and the measurement phase angle is corrected according to the system's preset transfer function to obtain the intrinsic phase angle reflecting the dielectric properties of the tissue. Thus, electrical impedance spectrum data within the preset frequency range are acquired. Based on the impedance spectrum data, frequency domain feature parameters reflecting the integrity of the cell membrane barrier are extracted. The frequency domain feature parameters include at least the variation characteristics of the impedance amplitude in the low frequency band relative to the high frequency band, and the dispersion of the phase angle in the low frequency band. The dispersion of the phase angle is used to quantify the attenuation of the polarization effect at the cell membrane interface. The frequency domain feature parameters are compared with the discrimination criteria constructed based on the specific impedance dispersion characteristics caused by cell membrane rupture due to freezing damage. The comparison results are used to determine whether the aquatic product under test has undergone freezing.

[0007] Furthermore, the preset frequency range at least covers the low-frequency band where cell membrane capacitance characteristics dominate tissue impedance characteristics, and the high-frequency band where intracellular fluid resistance dominates tissue impedance characteristics.

[0008] Furthermore, the multi-frequency composite excitation signal is generated by superimposing multiple sinusoidal signals of preset frequencies after phase encoding, and the initial phase of each frequency component is encoded to ensure that it can be uniquely identified in the time domain.

[0009] Furthermore, when correcting the measured phase angle, a phase synchronization correction factor related to the tissue impedance amplitude and the phase change gradient of adjacent frequency points is introduced to correct the nonlinear phase distortion introduced by contact state fluctuations, based on eliminating the inherent phase shift of the system.

[0010] Furthermore, when extracting frequency domain feature parameters, the electrical impedance spectrum data is inverted into a relaxation time distribution function, the statistical feature parameters of the relaxation time distribution function are extracted, and the statistical feature parameters are fused into a quantitative index characterizing the degree of tissue cryopreservation damage.

[0011] Furthermore, the statistical characteristic parameters of the relaxation time distribution function include at least the distribution center, distribution width, and distribution asymmetry, and the quantitative index is positively correlated with the degree of tissue cell membrane damage.

[0012] Furthermore, the discrimination criterion is implemented through a pre-constructed classification model, which is established based on the optimal distribution boundary of known fresh samples and known frozen samples in the frequency domain feature parameter space. The distribution boundary characterizes the impedance dispersion feature shift caused by cell membrane rupture due to freeze-thaw cycles.

[0013] Furthermore, the criteria for determining whether the aquatic product under test has undergone frozen storage are as follows: The impedance amplitude in the low-frequency band shows a specific decrease compared to the impedance amplitude in the high-frequency band. This specific decrease corresponds to the change in the conductive pathway caused by the irreversible rupture of the cell membrane due to ice crystal growth, which leads to the exchange of intracellular and extracellular fluid.

[0014] Furthermore, the muscle-rich area of ​​the aquatic product to be tested was selected as the measurement site. Before measurement, the area was kept naturally moist, and multiple measurements were performed at each preset frequency point. After outliers were removed, the average value was taken as the valid measurement data for that frequency point.

[0015] Secondly, a rapid and non-destructive system for determining whether aquatic products have been frozen is also provided, the system being based on the method described in the first aspect above, comprising: The measuring probe is configured to act on the muscle tissue of the aquatic product to be tested in a non-deformable compression contact manner, with the contact pressure provided solely by the probe's own weight, and employs a four-electrode configuration to apply excitation signals and pick up response signals. The signal conditioning unit integrates an automatic gain control module to dynamically adapt the excitation signal amplitude according to the strength of the response signal; The data processing unit is used to generate a phase-encoded multi-frequency composite excitation signal, synchronously extract the response signal of each frequency component using a phase-synchronous demodulation method, correct the measured phase angle according to the system's preset transfer function and phase synchronization correction factor to obtain the intrinsic phase angle, reconstruct the impedance spectrum within the preset frequency range, and extract frequency domain characteristic parameters reflecting the integrity of the cell membrane barrier. The discrimination unit has a built-in classification model based on the specific impedance dispersion characteristics caused by freezing damage, which is used to output the judgment result of whether the aquatic product under test has been frozen based on the frequency domain feature parameters.

[0016] This invention provides a rapid, non-destructive technical solution for determining whether aquatic products have undergone frozen storage based on multi-frequency bioelectrical impedance spectroscopy (BIS). The solution employs a non-deformation, pressure-contact four-electrode measurement configuration, applying multi-frequency excitation signals to the muscle tissue of the aquatic product under test. By separating the excitation and measurement circuits, the influence of contact interface impedance on signal accuracy is effectively eliminated. During data acquisition, the system monitors the signal response intensity in real time and dynamically adapts the excitation signal amplitude to ensure the signal remains within a linear dynamic range. Furthermore, by repeatedly acquiring data at multiple preset frequency points and removing outliers, the stability and repeatability of the impedance spectrum data are guaranteed. Based on the acquired impedance spectrum data, frequency domain characteristic parameters reflecting the integrity of the cell membrane barrier are extracted, including at least the variation characteristics of the impedance amplitude in the low-frequency band relative to the high-frequency band and the dispersion of the phase angle in the low-frequency band. The low-frequency measurement points are set in the frequency band where cell membrane capacitance characteristics dominate tissue impedance characteristics. These characteristic parameters are compared with a pre-constructed classification model, which is based on the distribution boundary of known fresh samples and known frozen samples in the characteristic parameter space. This distribution boundary characterizes the impedance dispersion shift caused by cell membrane rupture due to freeze-thaw cycles. By determining whether there is a specific decrease in the impedance amplitude in the low-frequency band, which corresponds to the change in the conductivity pathway caused by the irreversible rupture of the cell membrane due to ice crystal growth, the result of whether the aquatic product under test has undergone frozen storage is output.

[0017] Compared with existing technologies, this invention achieves the following beneficial effects: Through the synergistic effect of non-deformation compression contact and a four-electrode measurement configuration, the interference of contact pressure and interface impedance on measurement accuracy is effectively eliminated, ensuring the authenticity of the detection results; By combining automatic gain control with multiple repeated acquisitions and an outlier removal mechanism, the measurement system can adapt to differences in conductivity and contact state of different samples, significantly improving the measurement success rate; By extracting the variation characteristics of low-frequency impedance amplitude relative to high-frequency impedance and the degree of phase angle dispersion, the influence of individual differences and measurement condition fluctuations on the absolute impedance value is eliminated. Simultaneously, using the phase angle as an independent characterization parameter of cell membrane capacitance, it forms a multi-dimensional feature complement to the impedance amplitude, improving the discrimination model's ability to distinguish the degree of cell membrane damage; By setting the low-frequency measurement point at the cell membrane capacitance... The dominant frequency band enables the measurement results to have specific sensitivity to cell membrane structural damage caused by freeze-thaw cycles, while high-frequency measurement points provide a benchmark to eliminate the influence of non-specific factors, enhancing the accuracy of the discrimination criteria. By constructing a classification model based on the spatial distribution boundary of feature parameters, complex discrimination rules in the high-dimensional feature parameter space that are difficult to be reflected by a single threshold are explored, realizing the nonlinear boundary division of fresh and frozen samples, significantly improving the accuracy and generalization ability of the discrimination. The overall solution transforms the differences in the integrity of microscopic cell structures into quantitatively measurable macroscopic electrical signals, realizing full automation from signal acquisition to result output. While ensuring non-destructive testing, it also meets the technical requirements of speed, accuracy, and ease of operation, providing an effective technical solution for quality monitoring in the circulation of aquatic products.

[0018] Beneficial effects By implementing the rapid and non-destructive method for determining whether aquatic products have been frozen, provided by the present invention, the following technical effects are achieved: (1) By adopting a non-deformable compression contact method combined with a four-electrode measurement configuration, and monitoring the signal response intensity in real time during the acquisition process to dynamically adapt to the excitation signal amplitude, the non-deformable compression contact method avoids tissue deformation and measurement errors caused by changes in contact pressure. The four-electrode configuration effectively suppresses the interference of electrode-tissue interface polarization effect and contact impedance fluctuation on signal authenticity by separating the excitation and measurement circuits. Automatic gain control enables the measurement system to adapt to the conductivity differences and contact state changes of different samples, ensuring that the signal acquisition is always in the optimal linear working range.

[0019] (2) The variation characteristics of the impedance amplitude in the low-frequency band relative to the high-frequency band are extracted as the discrimination criterion, and the dispersion of the phase angle in the low-frequency band is introduced as an independent characterization parameter. Using the high-frequency impedance of the same measurement sample as the internal benchmark, the interference of individual differences and environmental factors on the absolute impedance value is eliminated, and the discrimination criterion is focused on the specific electrical fingerprint of cell membrane damage caused by freeze-thaw. At the same time, the dispersion of the phase angle, as an independent characterization of the cell membrane capacitance characteristics, forms a multi-dimensional feature complement to the impedance amplitude, which improves the discrimination model's ability to distinguish the degree of cell membrane damage and enhances the robustness of the discrimination.

[0020] (3) By applying a multi-frequency composite excitation signal using phase synchronization demodulation, the response signals at each frequency component are extracted synchronously, and the measured phase angle is corrected by combining the system's preset transfer function. This effectively eliminates the systematic and nonlinear interference of signal channel delay, electrode polarization effect, and contact state fluctuation on phase measurement, ensuring the accuracy of intrinsic phase angle extraction. The consistency between the phase angle dispersion curve and the tissue dielectric relaxation theory model is significantly improved, and the frequency domain continuity of phase measurement between multiple frequency points is maintained, providing high-fidelity input data for subsequent analysis of cell membrane interface polarization effects based on phase information.

[0021] (4) By inverting electrical impedance spectroscopy data into a relaxation time distribution function, statistical characteristic parameters such as distribution center, distribution width, and distribution asymmetry are extracted and integrated into a quantitative index characterizing the degree of tissue damage during cryopreservation. This extends the traditional binary discrimination model into a continuous quantitative assessment model, transforming the microstructural feature of cell membrane integrity into a measurable shift of the relaxation time distribution function in the parameter space. This significantly enhances the sensitivity of identifying early-frozen or slightly damaged samples, while also achieving a semi-quantitative assessment of cryopreservation time or number of freeze-thaw cycles. Attached Figure Description

[0022] To make the above-described method for rapid and non-destructive determination of whether aquatic products are frozen more apparent and understandable, the accompanying drawings used in the specific embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0023] Figure 1 This is a flowchart illustrating the method described in this application; Figure 2 Graphs showing impedance measurements at different frequencies for fresh and thawed black bass; Figure 3 A graph showing impedance measurements of fresh and thawed horse mackerel at different frequencies; Figure 4The graph shows the impedance measurements of fresh and thawed Izu scorpionfish at different frequencies. Figure 5 A graph showing impedance measurements of fresh and thawed bream at different frequencies; Figure 6 A graph showing the impedance comparison between fresh and thawed black bass at 2kHz. Figure 7 A graph showing the impedance comparison between fresh and thawed horse mackerel at a frequency of 2kHz. Figure 8 A graph showing the impedance comparison between fresh and thawed Izu scorpionfish at a frequency of 2kHz; Figure 9 This graph shows the impedance comparison between fresh and thawed bream at a frequency of 2kHz. Detailed Implementation

[0024] Example 1: This embodiment uses marine fish as the sample to be tested, and exemplarily illustrates the specific application process of the rapid and non-destructive method for determining whether aquatic products are frozen according to the present invention. Those skilled in the art should understand that this method is also applicable to freshwater fish and other aquatic products, and at the same time verifies the speed, non-destructive nature and field applicability of the method of the present invention.

[0025] This embodiment uses commercially available live sea bass as the core sample to be tested, and also adds horse mackerel, scorpionfish, and bream as universal verification samples for multiple fish species. Samples from the same batch were randomly divided into a fresh group and a freeze-thawed group. The fresh group was temporarily stored at 4°C for 2 hours after capture and tested within 6 hours; the freeze-thawed group was frozen at -20°C for 72 hours and then naturally thawed at 4°C until the core temperature reached 4°C before testing. Before testing, the area with abundant muscle above the lateral line on the back of the fish was selected as the measurement site. The surface moisture was gently wiped with a clean, soft cloth to remove excess fluid, keeping the measurement area naturally moist to avoid contact impedance variations introduced by dryness or excessive moisture.

[0026] The measurement system used in this embodiment is a handheld four-electrode bioelectrical impedance analyzer, which is built entirely based on the method of this invention and integrates four core modules: a measurement probe, a signal conditioning unit, a data processing unit, and a discrimination unit.

[0027] The measuring probe is configured to act on the muscle tissue of the aquatic product to be tested in a non-deformation compression contact manner. It adopts a four-electrode measurement configuration, with four gold-plated electrodes arranged linearly and equally spaced. The two outer electrodes are excitation electrodes used to inject excitation signals, and the two inner electrodes are measurement electrodes used to pick up response signals. By separating the excitation and measurement circuits, the interference of contact interface impedance and electrode polarization effect on measurement accuracy is effectively eliminated.

[0028] The signal conditioning unit integrates an automatic gain control module, which can monitor the signal response intensity in real time during the acquisition process, dynamically adapt the amplitude of the excitation signal, maintain the response signal within the preset linear dynamic range, and avoid signal saturation or insufficient signal-to-noise ratio. The data processing unit is used to reconstruct the impedance spectrum within the preset frequency range based on the acquired response signal and extract frequency domain feature parameters reflecting the integrity of the cell membrane barrier. The discrimination unit has a built-in discrimination model based on the specific impedance dispersion characteristics caused by cryopreservation damage, which can automatically output the determination result of whether the sample under test has undergone cryopreservation.

[0029] The full-process execution logic of the method of this invention is as follows: Figure 1 As shown, the process consists of three core steps: First, a non-deformable compression contact method is used to apply multi-frequency excitation signals to the muscle tissue of the aquatic product under test, and electrical impedance spectrum data within a preset frequency range is collected. Second, frequency domain feature parameters reflecting the integrity of the cell membrane barrier are extracted based on the electrical impedance spectrum data. These frequency domain feature parameters include at least the variation characteristics of the impedance amplitude in the low-frequency band relative to the high-frequency band. Third, the frequency domain feature parameters are compared with a discrimination criterion constructed based on the specific impedance dispersion characteristics caused by cell membrane rupture due to freezing damage. The comparison results are used to determine whether the aquatic product under test has undergone freezing.

[0030] The specific data acquisition process is as follows: The operator places the probe parallel to the selected measurement area on the back of the fish using a non-deformation pressure contact method. The contact pressure between the probe and the sample surface is provided by the probe's own weight; no external pressure exceeding its own weight is applied to avoid tissue deformation due to changes in contact pressure, which could affect the accuracy of impedance measurement. After the system starts, the signal generator generates a multi-frequency composite excitation signal, which is composed of the superposition of sine waves at multiple preset frequency points. The frequency range covers low-frequency, mid-frequency, and high-frequency bands. The low-frequency band is set in the frequency domain where cell membrane capacitance characteristics dominate tissue impedance characteristics, and the high-frequency band is set in the frequency domain where tissue dielectric characteristics are mainly dominated by intracellular fluid resistance. In this embodiment, the preset frequency points include 2kHz, 5kHz, 20kHz, 50kHz, and 100kHz, covering the core discrimination frequency band. The excitation signal is converted into a constant current with a safe amplitude by a voltage-controlled current source and injected into the tissue to be measured through the outer electrode. The inner electrode simultaneously picks up the response voltage signal.

[0031] During signal acquisition, the system monitors the intensity of the response voltage signal in real time and dynamically adapts the excitation current amplitude through an automatic gain control module to ensure that the response signal is always within the optimal linear dynamic range of the analog-to-digital converter. Simultaneously, a phase-synchronous demodulation method is employed to synchronously extract the response signals of each frequency component within the same time window. Based on a pre-stored system transfer function, the measured phase angle at each frequency point is corrected to eliminate systematic and nonlinear interference from signal channel delay, electrode polarization effects, and contact impedance fluctuations on the phase measurement, thus obtaining the intrinsic phase angle reflecting the dielectric properties of the tissue. Five repeated measurements are performed at each measurement frequency point. The system automatically removes outliers exceeding a preset multiple of the standard deviation from the mean using an algorithm, and then averages the results to ensure data stability and repeatability. Finally, multi-frequency impedance spectrum data of the sample under test within the preset frequency range are obtained.

[0032] Among them, the impedance measurements of fresh and thawed black bass at different frequencies are as follows: Figure 2 As shown, the impedance measurements of fresh and thawed horse mackerel at different frequencies are as follows: Figure 3 As shown, the impedance measurements of fresh and thawed Izu scorpionfish at different frequencies are as follows: Figure 4 As shown, the impedance measurements of fresh and thawed bream at different frequencies are as follows: Figure 5 As shown in the figure, the impedance spectrum measurement results of the above multi-fish species clearly show that the impedance amplitude of fresh samples is significantly higher than that of frozen-thawed samples in the low-frequency range, while in the high-frequency range, the difference in impedance amplitude between fresh and frozen-thawed samples is greatly reduced. This verifies the scientific validity and universality of the present invention, which uses the variation characteristics of impedance amplitude in the low-frequency range relative to the high-frequency range as the core discrimination criterion.

[0033] After data acquisition, the system integrates the complex impedance amplitude and intrinsic phase angle data at each frequency point into a multi-frequency impedance spectrum, which is then uploaded to the data processing unit to extract feature parameters. The core extraction focuses on the following three types of creative feature parameters with clear physiological mechanisms: The variation characteristics of low-frequency impedance amplitude relative to high-frequency impedance amplitude: The system calculates the rate of change of low-frequency impedance amplitude relative to high-frequency impedance amplitude, using the high-frequency impedance of the same measurement sample as an internal benchmark to eliminate the interference of non-specific factors such as individual differences, environmental factors, and contact conditions on the absolute impedance value, so that the discrimination criterion focuses on the specific electrical fingerprint of cell membrane damage caused by freeze-thaw. Among them, 2kHz is the core low-frequency band dominated by cell membrane capacitance characteristics. The impedance comparison of fresh black bass and thawed black bass at 2kHz is shown in Figure 6. The impedance comparison of fresh horse mackerel and thawed horse mackerel at 2kHz is shown in Figure 6. Figure 7 As shown, the impedance comparison between fresh and thawed Izu scorpionfish at 2kHz is as follows: Figure 8 As shown, the impedance comparison between fresh and thawed bream at 2kHz is as follows: Figure 9As shown above, the comparative results clearly demonstrate that the impedance amplitude of all fish species in the 2kHz low-frequency band showed a significant and specific decrease. This characteristic directly corresponds to the change in the conductive pathway caused by the irreversible rupture of the cell membrane due to ice crystal growth, which leads to the exchange of intracellular and extracellular fluids. This is the core specific electrical marker of cryopreservation damage.

[0034] Phase angle dispersion in the low-frequency band: This parameter is used to quantify the attenuation of the polarization effect at the cell membrane interface. As an independent characterization parameter of the cell membrane capacitance, it complements the impedance amplitude in a multidimensional feature, improving the ability of the discrimination model to distinguish the degree of cell membrane damage, especially enhancing the recognition sensitivity for short-term frozen or slightly damaged samples.

[0035] The system inputs impedance spectrum data into the relaxation time distribution inversion module, solves the relaxation time distribution function through a regularized inversion algorithm, and extracts statistical characteristic parameters such as distribution center, distribution width, and distribution asymmetry. These parameters are then fused into a relaxation damage index using a preset formula. This index quantifies the relaxation time broadening, distribution center shift, and asymmetric broadening caused by cell membrane rupture, extending the traditional binary discrimination mode into a continuous quantitative evaluation mode, which can achieve semi-quantitative evaluation of cryopreservation time and number of freeze-thaw cycles.

[0036] After the feature parameters are extracted, the system inputs them into the built-in discrimination model. The discrimination benchmark is realized through a pre-built classification model, which is a classifier built based on the support vector machine algorithm. It is obtained in advance through a large number of known fresh samples and known frozen samples. The optimal classification hyperplane for fresh samples and frozen samples is established in the feature parameter space. This distribution boundary accurately characterizes the impedance dispersion feature shift caused by cell membrane rupture due to freeze-thaw.

[0037] The model, based on multi-dimensional features such as the low-frequency relative impedance change rate, phase angle dispersion, and relaxation damage index, outputs the probability value of whether a sample belongs to the fresh or frozen category, and provides a final judgment result in conjunction with a preset confidence threshold. In this embodiment, after testing, the fresh group samples output a "fresh" judgment result with a confidence level higher than 95%; after testing, the freeze-thawed group samples output a "thawed" judgment result with a confidence level higher than 92%. The entire testing process, from probe contact with the sample to result output, takes no more than 5 seconds per test, and causes no physical damage or chemical contamination to the sample throughout the process. The tested samples are still safe to sell or consume.

[0038] Example 2: In bioelectrical impedance spectroscopy (BIP) measurements, the phase difference between the excitation and response signals not only contains information about the tissue's dielectric properties but is also affected by the measurement system's own channel delay, electrode polarization effects, and nonlinearity of the contact state. Existing methods typically employ a single-frequency sequential scanning approach, measuring each frequency independently, which fails to correct for inconsistencies in the system's phase response at different frequencies. This embodiment proposes a multi-frequency excitation signal measurement method based on phase-synchronous demodulation. By generating a phase-encoded multi-frequency composite excitation signal and applying it to the tissue under test, digital lock-in amplification (LIA) technology is used to perform phase-synchronous demodulation of the response signal to simultaneously extract the amplitude and phase information of each frequency component. The measured values ​​are then phase-corrected based on a pre-defined transfer function of the system. This method effectively separates the system's inherent phase shift from the tissue response phase shift, thereby extracting the intrinsic phase angle that reflects only the polarization effect at the cell membrane interface.

[0039] During system initialization, the measuring probe is placed against the selected measurement area on the back of the fish using a non-deformation, pressure-based contact method, keeping the contact interface naturally moist. The system control unit loads preset multi-frequency composite excitation signal parameters. This composite signal is composed of multiple frequency components superimposed, with the frequency values ​​of each component set in preset low-frequency, mid-frequency, and high-frequency bands. The initial phase of each frequency component is encoded to ensure that each frequency component can be uniquely identified by the digital lock-in amplifier in the time domain.

[0040] The signal generator generates a multi-frequency composite excitation current signal according to the set parameters. This signal is converted into a safe current by a voltage-controlled current source and injected into the tissue under test through the outer electrode of a four-electrode configuration. The inner electrode synchronously picks up the response voltage signal, which is a superposition signal of each frequency component after transmission through the tissue. Its amplitude attenuation and phase shift both carry information about the dielectric properties of the tissue.

[0041] The acquired response voltage signal, after pre-amplification and anti-aliasing filtering, is input to a multi-channel digital lock-in amplifier. The lock-in amplifier uses each frequency component of the excitation signal as a reference to demodulate the in-phase and quadrature components of the response signal, obtaining the initial values ​​of the real and imaginary parts of the complex impedance at each frequency point.

[0042] The system reads the pre-stored channel transfer function matrix, which is obtained through factory calibration or periodic self-calibration and records the inherent phase shift and amplitude attenuation coefficient of the measurement system at each frequency point. Based on this transfer function matrix, the initial values ​​of the complex impedance at each frequency point are corrected for system errors to eliminate the interference of channel delay and electrode polarization effects on phase measurement.

[0043] A phase synchronization correction factor is introduced, which is calculated using the following formula to characterize the mapping relationship between the intrinsic phase angle of the tissue and the measured phase angle of the system:

[0044] In the formula, To test the muscle tissue of the aquatic product at angular frequency The intrinsic phase angle below; For angular frequency The measured phase angle is obtained by demodulation using a digital lock-in amplifier. For measuring the system at angular frequency The system's inherent phase shift; These are organization type-related constants; For angular frequency The amplitude of the complex impedance obtained by measurement; These are organization type-related constants; This represents the gradient of the measured phase angle change between adjacent frequency points.

[0045] Based on the corrected intrinsic phase angle and the complex impedance amplitude, a complex impedance spectrum at multiple frequency points is constructed. This impedance spectrum is used as the basis for subsequent feature extraction and discriminant analysis, and is output to the data processing unit for further analysis.

[0046] To verify the technical effectiveness of this method, it was compared with the traditional single-frequency sequential scanning measurement method. The comparative experiment was set up as follows: 60 fresh marine fish samples from the same batch were randomly divided into a fresh group and a freeze-thawed group. The freeze-thawed group was subjected to standard freezing (-20℃ for 72 hours) and natural thawing before testing. Both groups of samples were tested under the same environmental conditions (temperature 20±1℃, humidity 60±5%), using the same four-electrode measurement probe, and impedance spectrum acquisition was performed using both the traditional single-frequency sequential scanning method and the phase-synchronous demodulation correction method. The measurement frequency range covered the low-frequency to high-frequency range, and each frequency point was measured 5 times. The experimental results showed that the traditional single-frequency sequential scanning method, due to the influence of tissue state drift and system channel delay during the measurement process, had a measurement standard deviation of 2.8° for the phase angle in the low-frequency range. The phase angle change curve between adjacent frequency points exhibited non-physical fluctuations, and the correlation coefficient with the theoretical dielectric relaxation model was only 0.82. After adopting the method, the standard deviation of phase angle measurement was reduced to 0.9°, a decrease of 67.9%. The correlation coefficient between the phase angle dispersion curve and the Cole-Cole theoretical model was improved to 0.97, and the coefficient of variation of continuous measurements at the same frequency point was reduced from 4.6% in the traditional method to 1.2%. In addition, the discrimination model based on the corrected impedance spectrum improved the accuracy of distinguishing between fresh and frozen samples from 86.7% in the traditional method to 96.5%. This indicates that by eliminating the inherent phase shift and nonlinear phase distortion of the system, this method significantly enhances the frequency domain consistency and repeatability of impedance spectrum measurements, providing a more reliable input data basis for subsequent discriminant analysis.

[0047] Example 3: The dielectric properties of biological tissues exhibit typical relaxation phenomena in the frequency domain, and this relaxation behavior is closely related to microstructural parameters such as cell membrane capacitance and intracellular and extracellular fluid resistance. Fresh fish muscle tissue has an intact cell membrane structure, and its dielectric relaxation behavior can be well described by a single relaxation time or a superposition model of a finite number of relaxation times. However, after cryopreservation, the cell membrane undergoes irreversible rupture, intracellular fluid flows out, and the tissue microstructure tends to homogenize, resulting in a dielectric relaxation spectrum characterized by relaxation time broadening and relaxation intensity decay. Existing methods typically extract only the impedance amplitude or phase angle at a single frequency as discriminant features, failing to fully utilize the relaxation spectrum information across the entire frequency range. This embodiment proposes a method for quantifying the degree of tissue damage based on relaxation time distribution. By inverting the measured impedance spectrum into a relaxation time distribution function, statistical characteristic parameters of the distribution function are extracted, including the distribution center, distribution width, and distribution asymmetry, as quantitative indicators characterizing the degree of cell membrane damage. This method transforms the microstructural feature of cell membrane integrity into the offset of the relaxation time distribution function in the parameter space, realizing continuous quantification of the degree of damage during cryopreservation rather than binary discrimination, and providing a more refined discrimination dimension for the identification of early cryopreservation or slightly damaged samples.

[0048] After completing the multi-frequency impedance spectrum acquisition and obtaining complex impedance data at each frequency point, the system inputs the impedance spectrum data into the relaxation time distribution inversion module. This module first preprocesses the impedance spectrum data, removing abnormal frequency points that deviate from the expected trend, and then uses an interpolation algorithm to extend the impedance data at discrete frequency points into smooth curves in the continuous frequency domain to improve the stability of subsequent inversions.

[0049] A tissue dielectric relaxation model is established. Based on the electrical properties of biological tissues, the complex impedance frequency domain response of tissues is expressed as an integral form of the relaxation time distribution function; that is, the impedance spectrum can be obtained from the relaxation time spectrum through a superposition kernel function transformation. This transformation relationship is based on an extension of the Cole-Cole model, introducing a distribution parameter to describe the broadening of the relaxation time.

[0050] The relaxation time distribution function is solved using a regularized inversion algorithm. Considering the limited and noisy impedance spectroscopy measurement data, this inversion problem is ill-conditioned and inverse, requiring the introduction of regularization constraints to obtain a stable solution. The Tikhonov regularization method is employed, incorporating both a fitting error term and a distribution function smoothness constraint term into the objective function. The regularization parameter is adaptively selected using a generalized cross-validation criterion to ensure that the inversion result both fits the measurement data and avoids excessive oscillations.

[0051] The characteristic parameters of the relaxation time distribution function are extracted. After inversion, the distribution function is represented as a continuous distribution curve with the logarithm of relaxation time as the abscissa. The system performs statistical feature analysis on this curve and extracts the following three core parameters: distribution center, i.e., the logarithm of relaxation time corresponding to the peak of the distribution function, reflecting the characteristic time of the main relaxation process of the tissue; distribution width, i.e., the full width at half maximum of the distribution function, quantifies the dispersion of relaxation time and is directly related to the uniformity of cell membrane integrity; and distribution asymmetry, i.e., the skewness coefficient of the distribution function, characterizes the tendency of the relaxation time distribution to shift towards higher or lower frequencies.

[0052] A relaxation damage index is introduced, which integrates the above three characteristic parameters into a single quantitative index using the following formula, to characterize the degree of tissue damage during cryopreservation:

[0053] In the formula, The relaxation damage index; The fusion coefficient is determined by training with multiple regression or machine learning methods based on the relaxation time distribution characteristics of a large number of known fresh and frozen samples. It is used to adjust the overall contribution weight of the relaxation time distribution width to the damage index. The width of the relaxation time distribution of the sample to be tested; The baseline distribution width for fresh samples; The distribution center of the sample to be tested; The baseline distribution center for fresh samples; The fusion coefficient is determined through training with a large number of known samples and is used to adjust the contribution weight of distribution asymmetry to the damage index, thereby controlling the influence of asymmetric features in the comprehensive index. This represents the degree of distribution asymmetry.

[0054] The calculated relaxation damage index is input as a feature parameter into the discrimination model. A larger index value indicates a more significant broadening of the relaxation time distribution, a greater shift in the distribution center, and stronger asymmetry, corresponding to more severe damage to the cell membrane of the corresponding tissue. The system compares this index with a preset damage threshold; when the index exceeds the threshold, it determines that the sample has undergone cryopreservation. Furthermore, the continuous change in the index value can provide a basis for semi-quantitative assessment of cryopreservation time or the number of freeze-thaw cycles, offering richer output information compared to traditional binary discrimination methods.

[0055] The relaxation damage index, along with the aforementioned impedance amplitude, phase angle, and other characteristic parameters, is input into a multidimensional discrimination model. Feature-level fusion further enhances the accuracy and robustness of the discrimination. The discrimination results, along with the relaxation damage index, are output to the human-computer interface, presented in a combination of numerical and graphical formats for operator reference.

[0056] To verify the effectiveness of this method, it was compared with the conventional single-frequency impedance threshold method. The comparative experiment was set up as follows: A total of 80 fresh marine fish samples from the same batch were selected. 40 fish served as a fresh control group for immediate testing, while the remaining 40 fish underwent standardized freezing treatment and were stored for different time gradients (24 hours, 48 ​​hours, 72 hours, and 120 hours, with 10 fish in each group). After freezing, all samples were naturally thawed and tested. All samples were measured under the same conditions, and discrimination analysis was performed using both the conventional single-frequency impedance threshold method (using impedance amplitude at 2kHz as the discrimination criterion) and the relaxation time distribution method. The experimental results showed that the conventional single-frequency impedance threshold method achieved an accuracy of 92.5% in distinguishing between fresh samples and samples frozen for more than 72 hours. However, for slightly damaged samples frozen for 24 hours and 48 hours, the misclassification rates were as high as 35.0% and 22.5%, respectively, indicating that the single-frequency impedance threshold method is insufficiently sensitive to early-stage frozen damage. After employing the aforementioned method, a relaxation damage index is constructed by inverting and calculating characteristic parameters such as the relaxation time distribution width, distribution center offset, and distribution asymmetry. The index ranged from 0.8 to 1.2 in fresh samples, increased to 1.6 to 2.1 in samples frozen for 24 hours, and reached 2.8 to 3.5 in samples frozen for 72 hours, showing a good dependence on freezing time. As a discrimination threshold, this method achieves an accuracy rate of 87.5% for samples frozen for 24 hours and 95.0% for samples frozen for 48 hours, representing improvements of 22.5 and 17.5 percentage points respectively compared to the conventional single-frequency impedance threshold method. Furthermore, the correlation coefficient between the relaxation damage index and freezing time reaches 0.94, significantly higher than the correlation coefficient (0.71) between impedance amplitude and freezing time using the conventional method. This indicates that the method of this invention not only achieves binary discrimination but also provides effective quantitative evidence for the semi-quantitative assessment of freezing time or freeze-thaw cycles, significantly expanding the information dimension and application value of the detection results.

Claims

1. A rapid, non-destructive method for determining whether aquatic products have been frozen, characterized in that, include: Using a non-deformable compression contact method where the contact pressure is provided solely by the probe's own weight, a multi-frequency composite excitation signal is applied to the muscle tissue of the aquatic product under test through a four-electrode measurement configuration. The excitation signal is injected through the outer electrode, and the response signal is picked up by the inner electrode. During the acquisition process, the signal response intensity is monitored in real time, and the amplitude of the excitation signal is dynamically adapted. The response signal at each frequency component is extracted synchronously using a phase-synchronous demodulation method, and the measurement phase angle is corrected according to the system's preset transfer function to obtain the intrinsic phase angle reflecting the dielectric properties of the tissue. Thus, electrical impedance spectrum data within the preset frequency range are acquired. Based on the impedance spectrum data, frequency domain feature parameters reflecting the integrity of the cell membrane barrier are extracted. The frequency domain feature parameters include at least the variation characteristics of the impedance amplitude in the low frequency band relative to the high frequency band, and the dispersion of the phase angle in the low frequency band. The dispersion of the phase angle is used to quantify the attenuation of the polarization effect at the cell membrane interface. The frequency domain feature parameters are compared with the discrimination criteria constructed based on the specific impedance dispersion characteristics caused by cell membrane rupture due to freezing damage. The comparison results are used to determine whether the aquatic product under test has undergone freezing.

2. The method according to claim 1, characterized in that: The preset frequency range covers at least the low-frequency band where cell membrane capacitance characteristics dominate tissue impedance characteristics, and the high-frequency band where intracellular fluid resistance dominates tissue impedance characteristics.

3. The method according to claim 1, characterized in that: The multi-frequency composite excitation signal is generated by superimposing multiple sinusoidal signals of preset frequencies after phase encoding. The initial phase of each frequency component is encoded to ensure that it can be uniquely identified in the time domain.

4. The method according to claim 1, characterized in that: When correcting the measured phase angle, a phase synchronization correction factor related to the tissue impedance amplitude and the phase change gradient of adjacent frequency points is introduced to correct the nonlinear phase distortion introduced by the contact state fluctuation, based on eliminating the inherent phase shift of the system.

5. The method according to claim 1, characterized in that: When extracting frequency domain feature parameters, the electrical impedance spectrum data is inverted into a relaxation time distribution function, the statistical feature parameters of the relaxation time distribution function are extracted, and the statistical feature parameters are fused into a quantitative index characterizing the degree of tissue cryopreservation damage.

6. The method according to claim 5, characterized in that: The statistical characteristic parameters of the relaxation time distribution function include at least the distribution center, distribution width, and distribution asymmetry, and the quantitative index is positively correlated with the degree of tissue cell membrane damage.

7. The method according to claim 1, characterized in that: The discrimination criterion is achieved through a pre-constructed classification model, which is based on the optimal distribution boundary of known fresh samples and known frozen samples in the frequency domain feature parameter space. The distribution boundary characterizes the impedance dispersion feature shift caused by cell membrane rupture due to freeze-thaw cycles.

8. The method according to claim 1, characterized in that, The basis for determining whether the aquatic product under test has been frozen is that the impedance amplitude in the low-frequency band shows a specific decrease compared to the impedance amplitude in the high-frequency band. This specific decrease corresponds to the change in the conductive pathway caused by the irreversible rupture of the cell membrane due to the growth of ice crystals, which leads to the exchange of intracellular and extracellular fluid.

9. The method according to claim 1, characterized in that: The muscle-rich area of ​​the aquatic product to be tested is selected as the measurement site. Before measurement, the area is kept naturally moist. Multiple measurements are performed at each preset frequency point. After outliers are removed, the average value is taken as the valid measurement data for that frequency point.

10. A rapid, non-destructive system for determining whether aquatic products have been frozen, characterized in that: The system is implemented based on the method described in any one of claims 1-9: The system includes: The measuring probe is configured to act on the muscle tissue of the aquatic product to be tested in a non-deformable compression contact manner, with the contact pressure provided solely by the probe's own weight, and employs a four-electrode configuration to apply excitation signals and pick up response signals. The signal conditioning unit integrates an automatic gain control module to dynamically adapt the excitation signal amplitude according to the strength of the response signal; The data processing unit is used to generate a phase-encoded multi-frequency composite excitation signal, synchronously extract the response signal of each frequency component using a phase-synchronous demodulation method, correct the measured phase angle according to the system's preset transfer function and phase synchronization correction factor to obtain the intrinsic phase angle, reconstruct the impedance spectrum within the preset frequency range, and extract frequency domain characteristic parameters reflecting the integrity of the cell membrane barrier. The discrimination unit has a built-in classification model based on the specific impedance dispersion characteristics caused by freezing damage, which is used to output the judgment result of whether the aquatic product under test has been frozen based on the frequency domain feature parameters.

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